class_docstr: Wavy objective function.
  
  This class defines the W / Wavy [1]_ global optimization problem. This is a
  multimodal minimization problem defined as follows:
  
  .. math::
  
      f_{\text{Wavy}}(x) = 1 - \frac{1}{n} \sum_{i=1}^{n}
                           \cos(kx_i)e^{-\frac{x_i^2}{2}}
  
  
  Where, in this exercise, :math:`k = 10`. The number of local minima is
  :math:`kn` and :math:`(k + 1)n` for odd and even :math:`k` respectively.
  
  Here, :math:`x_i \in [-\pi, \pi]` for :math:`i = 1, 2`.
  
  *Global optimum*: :math:`f(x) = 0` for :math:`x = [0, 0]`
  
  .. [1] Jamil, M. & Yang, X.-S. A Literature Survey of Benchmark Functions
  For Global Optimization Problems Int. Journal of Mathematical Modelling
  and Numerical Optimisation, 2013, 4, 150-194.
code: def fun(self, x, *args):
      self.nfev += 1
  
      return 1.0 - (1.0 / self.N) * sum(
          cos(10 * x) * exp(-(x**2.0) / 2.0)
      )
  
imports: from numpy import atleast_2d, arange, sum, cos, exp, pi
  from .go_benchmark import Benchmark
label_desc: Use image node_id 2 for calling the Wavy obj's underlying member method code with example usage: obj.fun(x) and returns: unknown